PropTech · Marketplace

Google Ads CAC of ₹12,000 per acquisition against a 14-month payback period, the business was economically underwater on every acquisition for over a year before recovering. ₹32L/month split between Google and Meta with no allocation logic tied to LTV. Optimising for lead volume: every form fill treated equally regardless of property value, broker intent, or conversion probability. 60% of acquired leads were converting at a lifetime value below their acquisition cost. No CRM-to-ad-platform feedback loop, campaigns had no signal on which leads became actual transactions.

Built a CRM-to-ad-platform feedback loop: tagged every closed transaction in the CRM with source campaign and ad group, then fed transaction values (not just lead counts) back into Google as offline conversions via GTM. Rebuilt Google Search campaigns to optimise for transaction value instead of lead volume, Smart Bidding with transaction value signals. Identified the three highest-LTV segments from CRM data (luxury residential, commercial leasing, NRI investors) and built separate campaign structures per segment with LTV-weighted audience seeds. Ran a 30-day budget hold-out on Meta to measure true incrementality before recommending reallocation.

CAC: ₹12,000 → ₹4,200 in 90 days after offline conversion feedback loop went live. CAC payback: 14 months → under 3 months. ROAS on LTV-positive cohorts: 5.2×. Two ad sets representing ₹7.4L/month in spend were cut after the offline conversion data showed zero closed transactions over 4 months. Google algorithm, now optimising for transaction value, naturally shifted spend toward the luxury residential and NRI segments, exactly where the highest-LTV customers had always been. The business moved from acquisition-economics-negative to positive within one quarter.